Axon calibers vary widely among different animals, neuron classes, and even within the same neuron. What determines the diameter of axon branches?

Fluorescence microscopy has evolved from a purely observational tool to a platform for quantitative, hypothesis-driven research. As such, the demand for faster and less phototoxic imaging modalities has spurred a rapid growth in light sheet fluorescence microscopy (LSFM). By restricting the excitation to a thin plane, LSFM reduces the overall light dose to a specimen while simultaneously improving image contrast. However, the defining characteristics of light sheet microscopes subsequently warrant unique considerations in their use for quantitative experiments. In this Perspective, we outline many of the pitfalls in LSFM that can compromise analysis and confound interpretation. Moreover, we offer guidance in addressing these caveats when possible. In doing so, we hope to provide a useful resource for life scientists seeking to adopt LSFM to quantitatively address complex biological hypotheses.

The rapid advancement of live-cell imaging technologies has enabled biologists to generate high-dimensional data to follow biological movement at the microscopic level. Yet, the "perceived" ease of use of modern microscopes has led to challenges whereby sub-optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill-advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image-processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with a discussion of how movement behavior can be mathematically modeled and described. © 2019 by John Wiley & Sons, Inc.

A large variability in performance is observed when participants recall briefly presented lists of words. The sources of such variability are not known. Our analysis of a large data set of free recall revealed a small fraction of participants that reached an extremely high performance, including many trials with the recall of complete lists. Moreover, some of them developed a number of consistent input-position-dependent recall strategies, in particular recalling words consecutively ("chaining") or in groups of consecutively presented words ("chunking"). The time course of acquisition and particular choice of positional grouping were variable among participants. Our results show that acquiring positional strategies plays a crucial role in improvement of recall performance.

The major site of in vivo transcriptional initiation for both heavy and light strands of human mitochondrial DNA is the displacement-loop region. Transcripts synthesized in vitro by human mitochondrial RNA polymerase were mapped to the nucleotide level and have identical 5’ end map positions to those reported for in vivo primary transcripts. An ordered series of deletion clones, whose template sequences were truncated at either the 5’ or 3’ end, was used to identify the precise mitochondrial DNA sequence required for initiation of transcription. The data provide a definitive assignment of the promoter for heavy-strand transcription occurring within -16 to +7 of the transcriptional start site 16 nucleotides upstream of the 5’ end of the gene for tRNAPhe and of the promoter for light-strand transcription occurring within -28 to +16 of the transcriptional start site at the 5’ end of "7S RNA." Within each control sequence is a candidate promoter whose consensus sequence is 5’-CANACC(G)CC(A)AAAGAPyA-3’ and in both cases transcriptional initiation occurs within six to eight nucleotides of the 3’ end of this sequence. The transcriptional start site is an integral part of each promoter and each promoter can function in the absence of the other.

In terrestrial vertebrates, sniffing controls odorant access to receptors, and therefore sets the timescale of olfactory stimuli. We found that odorants evoked precisely sniff-locked activity in mitral/tufted cells in the olfactory bulb of awake mouse. The trial-to-trial response jitter averaged 12 ms, a precision comparable to other sensory systems. Individual cells expressed odor-specific temporal patterns of activity and, across the population, onset times tiled the duration of the sniff cycle. Responses were more tightly time-locked to the sniff phase than to the time after inhalation onset. The spikes of single neurons carried sufficient information to discriminate odors. In addition, precise locking to sniff phase may facilitate ensemble coding by making synchrony relationships across neurons robust to variation in sniff rate. The temporal specificity of mitral/tufted cell output provides a potentially rich source of information for downstream olfactory areas.

Compared to the dorsal hippocampus, relatively few studies have characterized neuronal responses in the ventral hippocampus. In particular, it is unclear whether and how cells in the ventral region represent space and/or respond to contextual changes. We recorded from dorsal and ventral CA1 neurons in freely moving mice exposed to manipulations of visuospatial and olfactory contexts. We found that ventral cells respond to alterations of the visuospatial environment such as exposure to novel local cues, cue rotations, and contextual expansion in similar ways to dorsal cells, with the exception of cue rotations. Furthermore, we found that ventral cells responded to odors much more strongly than dorsal cells, particularly to odors of high valence. Similar to earlier studies recording from the ventral hippocampus in CA3, we also found increased scaling of place cell field size along the longitudinal hippocampal axis. Although the increase in place field size observed toward the ventral pole has previously been taken to suggest a decrease in spatial information coded by ventral place cells, we hypothesized that a change in spatial scaling could instead signal a shift in representational coding that preserves the resolution of spatial information. To explore this possibility, we examined population activity using principal component analysis (PCA) and neural location reconstruction techniques. Our results suggest that ventral populations encode a distributed representation of space, and that the resolution of spatial information at the population level is comparable to that of dorsal populations of similar size. Finally, through the use of neural network modeling, we suggest that the redundancy in spatial representation along the longitudinal hippocampal axis may allow the hippocampus to overcome the conflict between memory interference and generalization inherent in neural network memory. Our results suggest that ventral population activity is well suited for generalization across locations and contexts. © 2014 Wiley Periodicals, Inc.

Methods for one-photon fluorescent imaging of calcium dynamics can capture the activity of hundreds of neurons across large fields of view at a low equipment complexity and cost. In contrast to two-photon methods, however, one-photon methods suffer from higher levels of crosstalk from neuropil, resulting in a decreased signal-to-noise ratio and artifactual correlations of neural activity. We address this problem by engineering cell-body-targeted variants of the fluorescent calcium indicators GCaMP6f and GCaMP7f. We screened fusions of GCaMP to natural, as well as artificial, peptides and identified fusions that localized GCaMP to within 50 μm of the cell body of neurons in mice and larval zebrafish. One-photon imaging of soma-targeted GCaMP in dense neural circuits reported fewer artifactual spikes from neuropil, an increased signal-to-noise ratio, and decreased artifactual correlation across neurons. Thus, soma-targeting of fluorescent calcium indicators facilitates usage of simple, powerful, one-photon methods for imaging neural calcium dynamics.

COVID-19 has severely impacted socioeconomically disadvantaged populations. To support pandemic control strategies, geographically weighted negative binomial regression (GWNBR) mapped COVID-19 risk related to epidemiological and socioeconomic risk factors using South Korean incidence data (January 20, 2020 to July 1, 2020). We constructed COVID-19-specific socioeconomic and epidemiological themes using established social theoretical frameworks and created composite indexes through principal component analysis. The risk of COVID-19 increased with higher area morbidity, risky health behaviours, crowding, and population mobility, and with lower social distancing, healthcare access, and education. Falling COVID-19 risks and spatial shifts over three consecutive time periods reflected effective public health interventions. This study provides a globally replicable methodological framework and precision mapping for COVID-19 and future pandemics.

Determining cell identities in imaging sequences is an important yet challenging task. The conventional method for cell identification is via cell tracking, which is complex and can be time-consuming. In this study, we propose an innovative approach to cell identification during early C. elegans embryogenesis using machine learning. We employed random forest, MLP, and LSTM models, and tested cell classification accuracy on 3D time-lapse confocal datasets spanning the first 4 hours of embryogenesis. By leveraging a small number of spatial-temporal features of individual cells, including cell trajectory and cell fate information, our models achieve an accuracy of over 90%, even with limited data. We also determine the most important feature contributions and can interpret these features in the context of biological knowledge. Our research demonstrates the success of predicting cell identities in 4D imaging sequences directly from simple spatio-temporal features.